Study Programmes 2017-2018
Computer vision
Duration :
30h Th, 10h Pr, 50h Proj.
Number of credits :
Master in biomedical engineering (120 ECTS)5
Master in data science (120 ECTS)5
Master in electrical engineering (120 ECTS)5
Master of science in computer science and engineering (120 ECTS)5
Master in data science and engineering (120 ECTS)5
Master in computer science (120 ECTS)5
Lecturer :
Marc Van Droogenbroeck
Language(s) of instruction :
English language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Learning unit contents :
Contents: introduction, linear filtering and deconvolution, mathematical morphology, non-linear filtering, features extraction and border detection, texture, enhancement and restoration, shape analysis, image segmentation, motion detection, aspects of 3D vision, machine learning
Learning outcomes of the learning unit :
This course introduces to the major techniques used in image processing. Theoretical and practical aspects of image processing are discussed in details, with a focus on industrial applications.
At the end of the course, students will be able to:
  • master the notion of an image;
  • understand the major vision processing techniques;
  • design a complete video processing chain with a practical aim.
Exercise sessions, laboratory sessions and a large homework will help the students in developing more general skills like the capacity to evaluate tools, the conception of complete chain from the specifications to the realization, and team working.
Prerequisite knowledge and skills :
  • The student shall have passed a course on advanced programming.
  • The student shall be familiar with signal processing concepts.
Planned learning activities and teaching methods :
Apart from the theoretical course, there are :
  • exercise sessions
  • computer simulations
  • a large project (which is compulsory) consisting in a software implementation of computer vision techniques applied to a real situation
Mode of delivery (face-to-face ; distance-learning) :
It includes a lecture on theory and training session per week. The project must be delivered by the end of the first semester.
Recommended or required readings :
Slides :
Assessment methods and criteria :
Written exam which is compulsory except if the project has been rated with a note larger or equal to 10/20.
Homework (compulsory). This work must imperatively be given during the penultimate week of course of the first semester.
Methods of examination: The exam is composed of theoritical questions and exercises. This is an open-book exam.
Work placement(s) :
Organizational remarks :
Please note that the course is given in english!
Contacts :
Teacher : M. Van Droogenbroeck (04/366 26 93) Secretary : 04/ 366 26 91 Assistant : P. Latour